- Knows subsystem better than the CTO does
- Comfortable in graphics, embedded, or firmware
- math competition or research background
Forge currently processes every 3D CAD model and corresponding 2D drawing manually: one person reads the drawing, matches it to the CAD data, and validates the pair. Growing volume makes adding more manual reviewers non-scalable. This hire’s first project is to automate that matching and validation workflow.
The role works on computational geometry and CAD software with Walter, the technical lead. The initial scope is automating 3D-to-2D CAD matching and validation, followed by work on Forge’s geometry kernel, in-house CAD environment, and CNC toolpath engine. The single most important spike is developing enough technical depth to own a core subsystem end to end and eventually know that subsystem better than Walter.
What You'll Own
- Automate matching and validation between 3D CAD models and 2D drawings.
- Build and extend Forge’s geometry kernel and in-house CAD environment.
- Extend and eventually take ownership of the CNC toolpath engine that computes machine paths.
- Investigate open-ended computational-geometry and CAD research problems.
- Develop deep expertise in a core subsystem and own it end to end.
- Work closely with Walter and the engineering team to connect mathematical systems work to CNC manufacturing.
Technical Requirements
- Strong mathematics and computational-geometry fundamentals.
- Experience with CAD/CAM, 3D geometry, graphics, embedded systems, firmware, low-level systems, or related technical domains.
- Comfort reasoning about how computers operate at a low level rather than primarily building web applications.
- Ability to work on technically difficult geometry, CAD, and toolpath problems.
Execution and Ownership
- Can take on open-ended problems without a fixed stack or fully specified product plan.
- Can drive a subsystem from investigation through implementation and long-term ownership.
- Willing to develop expertise that exceeds the current technical lead’s depth in a subsystem.
- Can connect research-grade technical work to physical manufacturing outcomes.
Background
- 2–8 years of relevant experience. The transcript also states 2–6 years; confirm the intended range, with 2–8 preserved from the authoritative role details.
- A PhD is not required.
- Pedigree matters less for this role than demonstrated technical depth.
- Relevant backgrounds may include computational geometry, graphics, CAD/CAM, embedded systems, firmware, machine learning systems, or autonomous vehicles.
Location and Visa
- Toronto-based or willing to relocate to Toronto.
- Fully in person with a daily commute; remote and hybrid arrangements are not available.
- Visa sponsorship is not available.
Nice to Have
- Math competition experience such as AIME, USAMO, IMO, or Canadian equivalents.
- Undergraduate research in mathematics, computer science, engineering, or a related field.
- Machine learning or computer-graphics experience.
- Autonomous-vehicle experience involving open-ended, technically challenging problems.
- Production geometry or toolpath software experience.
- Experience at a semiconductor, GPU, or similarly deep-technical company.
Who Will Thrive Here Deep technical specialists who enjoy inventing foundational geometry and CAD systems rather than integrating existing libraries. This role suits someone who wants open-ended research, a direct connection between mathematical work and physical manufacturing, and the opportunity to become the company’s expert on a core subsystem. Candidates should be comfortable with fully in-person work and the schedule expectations, which require confirmation because the intake states both 9-9-5 and approximately 60 hours per week.